Proceedings chapter
OA Policy
English

Multimodal Analysis of Image Search Intent: Intent Recognition in Image Search from User Behavior and Visual Content

Presented atBucharest (Romania), June 06 - 09, 2017
PublisherACM Press
Publication date2017
Abstract

Users search for multimedia content with different underlying motivations or intentions. Study of user search intentions is an emerging topic in information retrieval since understanding why a user is searching for a content is crucial for satisfying the user's need. In this paper, we aimed at automatically recognizing a user's intent for image search in the early stage of a search session. We designed seven different search scenarios under the intent conditions of finding items, re-finding items and entertainment. We collected facial expressions, physiological responses, eye gaze and implicit user interactions from 51 participants who performed seven different search tasks on a custom-built image retrieval platform. We analyzed the users' spontaneous and explicit reactions under different intent conditions. Finally, we trained machine learning models to predict users' search intentions from the visual content of the visited images, the user interactions and the spontaneous responses. After fusing the visual and user interaction features, our system achieved the F-1 score of 0.722 for classifying three classes in a userindependent cross-validation. We found that eye gaze and implicit user interactions, including mouse movements and keystrokes are the most informative features. Given that the most promising results are obtained by modalities that can be captured unobtrusively and online, the results demonstrate the feasibility of deploying such methods for improving multimedia retrieval platforms.

Keywords
  • Multimedia
  • User interaction
  • Intent
  • Emotion
  • Experiment
  • Eye gaze
  • Facial expression
  • Computer vision
Funding
  • Swiss National Science Foundation - Ambizione
Citation (ISO format)
SOLEYMANI, Mohammad, RIEGLER, Michael, HALVORSEN, Pål. Multimodal Analysis of Image Search Intent: Intent Recognition in Image Search from User Behavior and Visual Content. In: ICMR ’17 Proceedings of the 2017 ACM on International Conference on Multimedia Retrieval. Bucharest (Romania). [s.l.] : ACM Press, 2017. doi: 10.1145/3078971.3078995
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Proceedings chapter (Published version)
Identifiers
Additional URL for this publicationhttp://dl.acm.org/citation.cfm?doid=3078971.3078995
ISBN978-1-4503-4701-3
693views
159downloads

Technical informations

Creation15/02/2018 13:48:00
First validation15/02/2018 13:48:00
Update time15/03/2023 07:52:18
Status update15/03/2023 07:52:17
Last indexation31/10/2024 09:37:02
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